Evidence map›Paper›PMID 34532484›Full record

ArticleAnnals of translational medicine2021

A prognostic staging system for light-chain amyloidosis using hepatic and renal indicator data from 1,064 Chinese patients.

Wei Yan, Yanze Cao, Aijun Liao, Wei Yang, Jian Li, Huihan Wang

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 44% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Wei YanDepartment of Hematology, Shengjing Hospital of China Medical University, Shenyang, China.
Yanze CaoNeusoft Research Institute, Northeastern University, Shenyang, China.
Aijun LiaoDepartment of Hematology, Shengjing Hospital of China Medical University, Shenyang, China.
Wei YangDepartment of Hematology, Shengjing Hospital of China Medical University, Shenyang, China.
Jian LiDepartment of Hematology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Huihan WangDepartment of Hematology, Shengjing Hospital of China Medical University, Shenyang, China.
China Medical University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNNortheastern University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLight-chain (AL) amyloidosis frequently involves severe multiple end-organ damage, thus affecting prognosis. As the current disease staging system is based only on cardiac indicators, we propose a new staging system based on multiple organ indicators to supplement the existing system.

methodsPatients with AL amyloidosis (n=1,064) from 18 Chinese hospitals were enrolled and divided into test and validation cohorts (4:1). Multivariate analyses were performed to identify the clinical and laboratory factors for inclusion in the new staging system.

resultsA score of 1 was assigned for each of the following-the difference between the involved and uninvolved free light chains ≥100 mg/L, estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m

conclusionsThe new staging system has been developed that incorporates plasma cell-related characteristics in addition to cardiac, renal, and hepatic function parameters. It enhances the risk stratification of patients with AL amyloidosis and is useful when multiple organs are involved.

Indexed as

hepatic functionLight-chain amyloidosisrenal functionstaging system

Identifiers

PMID34532484
PMCPMC8422138
OpenAlexW3194533800

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.